Over the last decades, the steady increase in the available number of television channels has caused users to be overwhelmed by the amount of available linear TV content, especially delivered in Internet Protocol TV (IPTV) service. The term “linear TV” refers to TV service in which the viewer has to watch a TV program at the particular time the program is broadcast and on the specific channel it is presented on. Sometimes the term “live TV” is used with reference to the above discussed “linear TV”. This increase made it hard to find TV content that would be relevant to the user amongst huge number of programs broadcast simultaneously. This results in random “channel surfing” behaviour where users scan for relevant content by hopping between different TV channels. The resulting user experience is inefficient (users will often miss interesting content) and therefore frustrating.
Existing audio-video content recommendation solutions focus mainly on on-demand content (e.g. NETFLIX or LOVEFILM), providing recommendations to the users; typically giving users the option to act on those recommendations, e.g. by clicking a recommended movie. Video services like YOUTUBE go one step further and construct personalized “channels” by concatenating recommended on-demand assets, operating without user intervention.
Companion services like www.zeebox.com offer simple analytics results for the popularity of linear TV content based on metrics like, for example, the number of tweets.